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KAIS
2008
221views more  KAIS 2008»
9 years 11 months ago
Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
Kun Zhang, Wei Fan
ICASSP
2010
IEEE
9 years 11 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classi´Čüer which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
10 years 29 days ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu
ICML
2004
IEEE
11 years 10 days ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
GIS
2008
ACM
11 years 18 days ago
Pedestrian flow prediction in extensive road networks using biased observational data
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...
Michael May, Simon Scheider, Roberto Rösler, ...
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